This invention relates to a method for spatial imaging of neuronal biological material using diffusion based magnetic resonance imaging (MRI) techniques.
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Magnetic Resonance Imaging (MRI) is the major imaging technique for non-invasive detection of early and fine neuronal disorders and degenerative process. Among the various MRI techniques employed, measuring the diffusion of water in neuronal systems seems to be very promising for differentiating between different tissue compartments and pathologies. By using a modification of the pulsed gradient spin echo (PGSE) method one can generally measures diffusion in MRI. In this method, two pulsed magnetic field gradients separated by a time interval called the diffusion time Td are employed. Diffusion of water molecules during the diffusion time causes signal attenuation according to the Stejskal-Tanner Equation [1] (Ref. 1):
ln(Ig/I0)=xe2x88x92xcex32g2xcex42(xcex94xe2x88x92xcex4/3)D=xe2x88x92bDxe2x80x83xe2x80x83[1]
where Ig and I0 represent the echo intensities in the presence and absence of diffusion gradients, xcex3 is the gyro-magnetic ratio, g is the pulsed gradient amplitude, xcex4 is the pulsed gradient duration, xcex94 is the time separation between the leading edges of these gradients, D is the diffusion coefficient and the b value represents the overall diffusion weighting in the diffusion experiment. In equation [1] the diffusion time Td is determined as (xcex94xe2x88x92xcex4/3). A genuine mono-exponential relation as described above is true only for a single population exhibiting free unrestricted diffusion. Such a case cannot be assumed, a priori, for any biological tissue where the observed signal is generally a superposition of several signals from several different environments. Thus the interpretation of a NMR signal attenuation arising from diffusion in biological tissued is complex and rather difficult. The complexity and difficulty arises from the fact that the signal may originate from water molecules in different compartments which might exchange in different rate between the different environments within the experimental diffusion time. In addition, some restriction due to barriers and membranes may also prevail in some environments. Therefore in MRI one refers to the apparent diffusion coefficient (ADC) rather than to the self-diffusion coefficient D (Ref 2). Nevertheless, water diffusion measurements serve as an important technique for detecting and characterizing various brain pathologies, i.e. ischemia, trauma, tumors as well as other disorders (spreading depression).
The white matter of the brain is located in the central and subcortical region of the cerebral and cerebella hemispheres and accounts for about 60% of the total brain volume. The white matter includes the major comiseral tract, the cortical association fibers, and all the corticals afferent and efferent fibers. Etiologically, the white matter contains nerve fibers, supporting cells, interstitial states and vascular structures. White matter consists mostly of axons with their envelope of myelin along with two types of neuro-ganglia, oligo dendrocytes and astrocytes. Axons are the extensions of neurons that reside within the gray matter of the brain, spinal cord and ganglia. The myelin sheaths are produced and maintained by the oligo dendrocytes. Myelin functions as an isulator of the axon, and its structure facilitates rapid transmission of neuronal impulses. Myelin is therefore crucial for normal function of the nervous system. It should be noted also that myelin in largely absent in the CNS of newborn and its amount in the CNS increases with maturation. Therefore the integrity of the myelin in the developing CNS may serve as a marker of normal maturation on the one hand, and for degenerating processes on the other. Both developing disorders in the nervous system and many degenerating processes involving the white matter cause damage to the myelin network in the nervous system.
Multiple Sclerosis (MS) that is an autoimmune mediated disease of the central nervous system is such an example. The disease is characterized by demyelination of axons leading to the formation of multiple sclerosis lesions. Clinical diagnosis of MS is done most frequently by MRI utilizing the techniques of T2-weighted MRI and Fluid Level Attenuated Inversion Recovery (FLAIR). However, usually there is no correlation between the severity of the disease and the clinical state of the patient as revealed by the T2-weighted or FLAIR MRI techniques (Ref. 3). This lack of correlation, termed as xe2x80x9cclinico-radiological paradoxxe2x80x9d may suggest that the existing MRI techniques do not identify the whole pathological picture in MS (Ref. 4). This lack of correlation is further demonstrated by the fact that areas, that appear by the existing MRI techniques to be normal, and therefore termed as normal appearing white matter (NAWM), show abnormal metabolite distribution as deduced from magnetic resonance spectroscopy (MRS) (Ref. 4). One of the main disadvantages of MRI techniques is their lack of specificity. This may be the cause for the inability of conventional MRI techniques to detect some MS white matter abnormalities. Thus there is a strong need for developing a reliable MRI technique that will be more specific to white matter disorders in general and to the myelin integrity in particular, and that will demonstrate more accurately the clinical situation in white matter associated disorders and that will allow to follow white matter maturation in a more specific way.
The present invention is based on the finding that at high b values the water signal decay is non mono-exponential in neuronal tissue and that at least two diffusion components could be identified both in brain tissues, optic nerve and spinal cord (Ref. 5-8). The slow diffusing components of the water signals in these tissues were shown to be related to the axonal milieu (Ref. 6-7). It is suggested in the present invention that in the context of white matter pathologies (maturation and/or degeneration) the slow diffusing component, never analyzed until the present invention, holds higher diagnostic capacity since its reflects better the integrity of the myelin in said tissue samples or organs.
Equation [1] cannot describe a mono-exponential signal decay, therefore analysis of a diffusion weighted MRI based on high b values requires a different approach. An approach termed as q-space diffusion NMR gives the displacement distribution function of water molecules for a certain diffusion time. This displacement distribution function can be characterized by various parameters an example being the following two parameters: the mean displacement and the probability for zero displacement. By a preferred embodiment of the present invention these two parameters are used to obtain two separate MR images that reflect, inter alia, the integrity of the myelin in the examined sample or organ.
Thus in accordance with the present invention it was found that by analyzing the diffusion characteristics of the slow diffsion component of water, corresponding to diffusion in restricted compartments in neuronal white matter, it is possible to detect white matter abnormalities. By utilizing this approach it was possible to detect the white matter damage caused by chronic hypertension in rat spinal cord and to differentiate between white matter in healthy controls and in diseased NAWM of MS patients. The slow diffusion component of water in such tissue originated mainly from diffusion of water in myelin-coated axonal matter, which serves as a compartment for restricted diffusion of water. Alteration in said coating, changes the exchange of water between the cellular compartments and affect the amount of restriction, and thus has a marked effect on said slow diffusion component. Therefore such analysis has a high diagnostic ability towards MS and other white matter-associated disorders.
Thus the present invention concerns a method for the spatial imagine of neuronal white matter the method comprising:
(i) exposing a region of the neuronal white matter to a gradient-varying series of diffusion weighted MRI sequences, the parameters of said MRI sequence being such so as to produce a plurality of non mono-exponential decay signals;
(ii) analyzing said non mono-exponential decay signals so as to obtain a parameter reflecting the diffusion characteristics of the slow diffusing component;
(iii) forming an array of said parameters characterizing the slow diffusing water component thereby obtaining the spatial image of said region of the neuronal white matter.
The array may be a 2 or 3 dimensional array.
In a preferred embodiment the analysis is carried out by the q-space analysis.
The term xe2x80x9cneuronal white matterxe2x80x9d refers to neuronal tissue in the central nervous systems (CNS) and the peripheral nervous system (PNS) that has a predominant component of myelin coated axons such as brain tissue, spinal cord or peripheral nerves such as the sciatic nerve. This term is meant to encompass tissues that contain exclusively myelin coated axons such as in the spinal cord, fiber tracts in brain as well as neuronal tissue which contains in addition to such axons cell bodies of neuronal, or non-neuronal cells (such as astrocytes) an example of the latter being the brain tissue.
The spatial imaging of the neuronal white matter may be done for a plurality of reasons. By one option, it is carried out to follow normal and abnormal brain maturation and degeneration.
By another option it is carried out for the diagnosis of a variety of diseases and pathologies involving white matter that may be due to various genetic, infectious, or inflammatory or other acquired conditions. Typically the diagnosis is achieved by comparing the image obtained from the disease individual with a corresponding image obtained from a healthy control, difference between the two images indicating region of disease neuronal white matter.
Examples of such diseases are:
Abnormal white matter maturation in newborn and children caused by various genetic, infectious, or inflammatory or other acquired conditions. These other acquired conditions may be malnutrition, birthth asplaxia, hypoxia and strokes.
Leukoystrophies, such as ALD (adrenoleukodystrophy), neonatal ALD, Aicardi-Goutieres Syndrome, Alexander Disease, CACH (Vanishing White Matter Disease), CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), Canavan Disease (Spongy Degeneration), CTX (Cerebrotendinous Xanthomatosis), Krabbe Disease (Globoid Cell Leukodystrophy), Metachromatic Leukodystrophy, Ovarioleukodystrophy Syndrome, Pelizaeus- Merzbacher Disease, Refsum Disease, Van der Knapp Syndrome, Zellweger Syndrome;
Demyelinating diseases: deep white matter iscehmia (resulting from cerebrovascular disease, hypertension and aging), Vascular dementia, Multiple Sclerosis;
Infectious and inflammatory disorders: progressive multifocal leukco-encephalopathy (PLM), post infectious encephalitis, HIV encephalitis, radiation injury;
Acquired toxic metabolic disorders: caused by chemotherapeutic agents, immunosuppressant agents, and central post time myelinolysis.
Demyelinating diseases of the peripheral nervous system: Allergic Neuritis, Guillain-Barre Syndrome (GBS).
It should be understood that any pathology that may affect the white matter fiber tract such as tumors or stroke, may also be detected and monitored by the present method.
By another option, the imaging may be carried out for basic science research reasons, such as for monitoring normal physiological changes which occur in the peripheral and central nervous system, for example during neonatal development and during aging.
The imaging technique of the present invention may also be used to monitor therapeutic intervention, and to determine the success of various therapeutic modalities in affecting the above diseases, as well as other diseases connected to degeneration and regeneration of neuronal matter.
The term xe2x80x9cgradient-varying seriesxe2x80x9d refers to sequences in which either the gradient strength or the gradient duration are varied in a way which enable to characterize the diffusion of water molecule in said examined region.
The term xe2x80x9cdiffusion-weighted MRI sequencesxe2x80x9d refers to a plurality of Magnetic Resonance pulse sequences enabling the production of an image of a certain region in a sampled organ, based on the measurements of the diffusion of water molecules. The plurality of said diffusion sequences may include variation of spin echo, gradient echo and stimulated echo diffusion MRI sequences. These may be acquired using the multi-shot or the single shot approaches such as in FLASH or echo planar diffusion NM sequences (diffusion EPI) or any variants thereof. Other sequences may be fast spin echo diffusion or any other modification thereof. The parameters of the MRI sequences should be such that the signal decay of water molecules produced therefrom are not mono-exponentialxe2x80x94i.e. that they contain at least two exponential signal decays.
The term xe2x80x9cnon mono-exponentialxe2x80x9d refers to at least a bi-exponential decay signal or to a non-exponential decay signal superimposed with a mono- or higher exponential signals. The first, fast exponential decay signal is attributed to free and unrestricted diffusion of water molecules in relatively large compartments, such as cell bodies that may exchange with the extra-cellular matrix. The non mono-exponential decay signal is a supervision of a plurality of signal decays caused by water molecule diffusion, obtained from several compartments, wherein the slow diffusion component is attributed to water diffusion in white matter components. Diffusion of water in this compartment is restricted due to its small size and due to the presence of the myelin sheaths.
According to the present invention, different methods of analysis that provide characterization of the slow diffusing water component may be used. Parameters such as the ADC and for example the population size of the slow diffusing component may be used to construct the image.
By a preferred embodiment, the non mono-exponential signal decay is analyzed by the q-space approach that provides displacement distribution function from which the mean displacement and the probability for zero displacement can be extracted.
This is typically done by a Fourier transformation (FT) of the signal decay as a function of the q values (defined as q=xcex3xcex4g/2xcfx80) with respect to q (Ref. 9 and 10). Such transformation minimizes the contribution of the first fast diffusing component of water that is much less specific to neuronal white matter.
Once a displacement distribution function is obtained after said transformation, it is possible to isolate therefrom at least one diffusion parameterxe2x80x94being a single parameter, characterizing the ability of water to diffuse in the sampled region. By one embodiment, the diffusion parameter is the mean displacement of water, being the width at half a height of the displacement distribution profile or any function of or obtained from the q-space analysis.
By another embodiment the diffusion parameter is the probability for zero displacement being the peak intensity of said displacement distribution profile.
By a preferred embodiment both of the above diffusion parameters are obtained to form two sets of parameters.
The diffusion parameters of each set (for example the mean displacement and the probability for zero displacement) are then arranged in an array, which gives the spatial image of the region of the neuronal white matter sampled. If more than one diffusion parameter is isolated, more than one MR image is obtained.
Where for example the region of the neuronal white matter is composed mainly from axons having a known arrangement (for example axons present in the spinal cord), it is possible to expose the sampled region of the white neuronal matter to a gradient-varying series of diffusion weighted MRI sequences in a single direction, where the direction of the diffusion sensitizing gradients is normal to the direction of the spinal cord.
In other applications where only the general direction of the fibers are known it is preferred to perform the measurements using diffusion sensitizing gradients along the three cartesian axes (x, y and z) and extract the contribution from the diffusion normal to the direction of the long axis of the fibers.
However, in the case in a spatial image of a complicated, non-linearly arranged white matter (such as in the brain), it is preferable in accordance with the method of the invention, to expose the region of the neuronal white matter to gradient-varying series of diffusion weighted MRI sequences in at least six different directions as proposed by Basser (Ref. 11). In neuronal white matter in the brain, it is preferable to use six or more different directions of diffusion sensitizing gradient-varying series of diffusion weighted MRI.